DEFI

Three major challenges faced by DeFi lending protocols! If resolved, massive funds from traditional institutions could enter the market.

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Three major challenges faced by DeFi lending protocols! If resolved, massive funds from traditional institutions could enter the market.

The research analyst at DeFi Cheetah pointed out three main issues with current DeFi lending protocols, namely "interest rates are not random", "inefficient loans based on utilization", and "lack of composability in credit risk". Until these issues are addressed, traditional institutions are unable to price the risk of lending protocols, thus preventing the inflow of traditional finance into the chain.

This is a translation and summary of the key points, for reference please see the original text below.

3 Issues to Be Resolved in DeFi Lending Protocols

According to DeFi Cheetah, the 3 main issues are:

  1. Interest rates are not random.
  2. Lending efficiency based on utilization is low.
  3. Credit risk is not composable.

DeFi Cheetah believes that the primary impact of these 3 issues lies in the inability to achieve risk pricing related to fixed income, insurance, or interest rate markets without institutional funds. When there is a significant difference between this market and the actual market, institutions do not know how to price these risks.

Issue 1: Interest Rates Are Not Random in DeFi Lending Protocols

Regarding the first point, it concerns how the borrowing rate is determined in lending protocols. The fluctuation of the utilization rate of the lending pool will have a corresponding impact on the borrowing rate. Therefore, regardless of market conditions, the borrowing rate is predetermined, and the corresponding borrowing rate can be calculated as long as there is utilization data.

Using Aave's borrowing rate definition as an example, where Optimal UR and other parameters are manually set, the lending rate is a function of the borrowing rate and the utilization rate. Based on the formula, high utilization leads to higher rates, creating an imbalanced nominal/principal matching mechanism that results in lower efficiency.

DeFi Cheetah points out that the market is only random when lenders and borrowers enter/exit the market at different market clearing rate levels, driving rates up or down based on their randomness in entering/exiting the currency market.

Why do complex risk pricing models in finance assume that interest rates are random?

"In financial markets, participants have different intentions for transactions, and these intentions change rapidly with the availability of information. The order or speed at which they change perspectives also changes. Therefore, interest rates are random, unlike in DeFi lending, where rates are determined or predictable," said DeFi Cheetah.

Due to many phenomena not being deterministic - if X happens, then Y will happen - but probabilistic, risk pricing based on random interest rates can effectively incorporate probabilistic factors into financial models, producing results distributed within a range.

Issue 2: Low Lending Efficiency Based on Utilization in DeFi Lending Protocols

Regarding the second issue, DeFi Cheetah states that the lending method based on utilization is inefficient. The market is only in equilibrium when the utilization is at 100%, where the borrowing rate equals the lending rate.

For example, in a fund pool with a 50% utilization rate and a 5% borrowing rate, the borrowing rate would be 5% * 0.5 = 2.5%. The 2.5% spread between borrowing and lending rates is a deadweight loss that cannot be captured by the lending protocol or borrowers, resulting in wastage.

In economics, deadweight loss typically refers to the inefficient allocation of resources due to factors such as monopoly pricing or government taxes.

In lending protocols, the inefficiency arises from the different borrowing rates, where borrowers pay higher rates while lenders receive lower rates. However, this spread is not captured by the lending protocol but wasted.

Using ETH and wBTC on Aave as an example, the lending spread for both assets exceeds 1.5%, with borrowing rates even surpassing lending rates by 50%! This situation limits the protocol's ability to earn a significant portion from borrowing rates, as widening the spread would lead to lower efficiency. Making lending activities more efficient is crucial for the protocol to earn more fees.

Issue 3: Lack of Composability in Credit Risk in DeFi Lending Protocols

For the third point, theoretically, interest rate differentials between lending protocols can be narrowed through arbitrage strategies. For example, assuming Aave's borrowing rate is 2% and Compound's lending rate is 7%.

  1. User borrows 10 million USDC from Aave.
  2. Deposits USDC into Compound to receive 10 million cUSDC.
  3. Uses cUSDC as collateral on Aave and repeats the borrowing process.

By continuously repeating these actions, users can arbitrage the rate differential between the two protocols until Aave's borrowing rate aligns with Compound's lending rate.

However, this arbitrage behavior is currently not feasible because Aave does not accept Compound's cUSDC as collateral, and vice versa.

The Future of DeFi Lending Protocols

These are the 3 main issues that DeFi Cheetah believes DeFi lending protocols currently face. They hope that innovative methods can be developed to create yield curves composed of bonds with different tenors, serving as a benchmark for risk pricing, and potentially attracting substantial funds to institutional currency markets on the chain.